CERN-EP-2018-310 2019/04/09
CMS-TOP-17-008
Measurement of the top quark mass in the all-jets final state
at
√
s
=
13 TeV and combination with the lepton+jets
channel
The CMS Collaboration
∗Abstract
A top quark mass measurement is performed using 35.9 fb−1 of LHC proton-proton collision data collected with the CMS detector at √s = 13 TeV. The measurement uses the tt all-jets final state. A kinematic fit is performed to reconstruct the decay of the tt system and suppress the multijet background. Using the ideogram method, the top quark mass (mt) is determined, simultaneously constraining an additional
jet energy scale factor (JSF). The resulting value of mt = 172.34±0.20 (stat+JSF)±
0.70 (syst) GeV is in good agreement with previous measurements. In addition, a combined measurement that uses the tt lepton+jets and all-jets final states is pre-sented, using the same mass extraction method, and provides an mt measurement
of 172.26±0.07 (stat+JSF)±0.61 (syst) GeV. This is the first combined mt extraction
from the lepton+jets and all-jets channels through a single likelihood function.
Published in the European Physical Journal C as doi:10.1140/epjc/s10052-019-6788-2.
c
2019 CERN for the benefit of the CMS Collaboration. CC-BY-4.0 license
∗See Appendix A for the list of collaboration members
1
Introduction
The top quark [1, 2] is the most massive known fundamental particle and its mass mt is an
important parameter of the standard model (SM) of particle physics. Precise measurements of mt can be used to test the internal consistency of the SM [3–5] and to search for new physical
phenomena. Since the top quark dominates the higher-order corrections to the Higgs boson mass, a precise mtdetermination is crucial to put constraints on the stability of the electroweak
vacuum [6, 7].
At the CERN LHC, top quarks are predominantly produced in quark-antiquark pairs (tt) through the gluon fusion process, and decay almost exclusively to a bottom quark and a W bo-son. Each tt event can be classified through the decays of the W bosons. Events in the all-jets final state correspond to those that have both W bosons decaying further into qq0 pairs, while events in the lepton+jets final state have one W boson decaying to a charged lepton and a neutrino.
This paper presents a measurement of mtobtained in the tt all-jets decay channel using
proton-proton (pp) collision data taken in 2016 by the CMS experiment at a center-of-mass energy of
√
s = 13 TeV, corresponding to an integrated luminosity of 35.9 fb−1. The two bottom quarks and the four light quarks from the tt decay are all required to be physically separated in the lab-oratory frame of reference, and the nominal experimental signature is therefore characterized by six jets in the detector.
Although this final state provides the largest branching fraction of all tt decays, this measure-ment of mtis particularly challenging, because of the large background from multijet
produc-tion. A kinematic fit of the decay products to the tt hypothesis is therefore employed to separate signal from background events.
The value of mt is extracted using the ideogram method [8, 9], which is based on a
likeli-hood function that depends either just on the mass parameter mt, or on mtcombined with an
additional jet energy scale factor (JSF). In the second case, the invariant mass of the two jets associated with the W→qq0decay serves as an observable to directly estimate the JSF.
Previous measurements in this decay channel have been performed by Tevatron and LHC ex-periments at lower center-of-mass energies [10–14]. The most precise one of these has been obtained by CMS at √s = 8 TeV, resulting in a mass of mt = 172.32±0.25 (stat+JSF)±
0.59 (syst) GeV. Combining the results of several measurements using different final states at√s = 7 and 8 TeV, ATLAS and CMS reported values of mt = 172.69±0.48 GeV [15] and
172.44±0.48 GeV [12], respectively, while a value of mt = 174.30±0.65 GeV was obtained by
combining the Tevatron results [16].
The top quark mass has been measured for the first time with pp data at√s = 13 TeV, using the lepton+jets channel [17], yielding a value of mt=172.25±0.08 (stat+JSF)±0.62 (syst) GeV.
A measurement using both tt all-jets and lepton+jets events is presented here. This is possi-ble since the two measurements use the same mass extraction method, so a single likelihood can be used, rather than just combining the two results statistically. With this approach, no assumptions on correlations between different uncertainties of the measurements have to be made. This is the first report of a combined mtmeasurement in the lepton+jets and all-jets final
2
The CMS detector and event reconstruction
The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diame-ter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintilla-tor hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity (η) coverage provided by the barrel and endcap detec-tors. Muons are detected in gas-ionization chambers embedded in the steel flux-return yoke outside the solenoid.
Events of interest are selected using a two-tiered trigger system [18]. The first level, composed of custom hardware processors, uses information from the calorimeters and muon detectors to select events within a time interval of 4 µs, resulting in a trigger rate of around 100 kHz. The second level, known as the high-level trigger (HLT), consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing, and reduces the event rate to around 1 kHz before data storage.
The particle-flow (PF) algorithm [19] aims to reconstruct and identify each individual particle in an event, with an optimized combination of information from the various elements of the CMS detector. The energy of photons is obtained from the ECAL measurement. The energy of electrons is determined from a combination of the electron momentum at the primary in-teraction vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track. The energy of muons is obtained from the curvature of the corresponding track. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for zero-suppression effects and for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL energy.
The reconstructed vertex with the largest value of summed physics-object p2Tis taken to be the primary proton-proton interaction vertex. The physics objects are the jets, clustered using the jet finding algorithm [20, 21] with the tracks assigned to the vertex as inputs, and the associated missing transverse momentum, taken as the negative vector sum of the transverse momentum pT of those jets.
Jets are clustered from PF objects using the anti-kT algorithm with a distance parameter of
0.4 [20–22]. Jet momentum is determined as the vectorial sum of all particle momenta in the jet, and is found from simulation to be within 5 to 10% of the true momentum over the whole pT spectrum and detector acceptance. Additional proton-proton interactions within the same
or nearby bunch crossings (pileup) can contribute additional tracks and calorimetric energy depositions to the jet momentum. To mitigate this effect, tracks identified to be originating from pileup vertices are discarded, and an offset correction is applied to correct for remaining contributions from neutral hadrons. Jet energy corrections (JECs) are derived from simulation to bring the measured response of jets to that of particle level jets on average. In situ measure-ments of the momentum balance in dijet, photon+jet, Z+jet, and multijet events are used to ac-count for any residual differences in the jet energy scale in data and simulation [23]. Additional selection criteria are applied to each jet to remove jets dominated by anomalous contributions from various subdetector components or reconstruction failures [24].
A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [25].
3
Event selection and simulation
Only jets with pT > 30 GeV reconstructed within |η| < 2.4 are used in the analysis. For the
identification of jets originating from the hadronization of b quarks, the combined secondary vertex algorithm (CSVv2) b tagger is used [26]. The chosen working point provides an identi-fication efficiency of approximately 50% with a probability of misidentifying a u/d/s quark jet or gluon jet as being a bottom jet of approximately 0.1%, and a misidentification probability for c quark jets of 2%. The hadronic activity, used for the event selection, is defined as the scalar pT sum of all jets in the event,
HT ≡
∑
jetspT.
Data events are selected using an HLT that requires the presence of at least six PF jets with pT >40 GeV and HT >450 GeV. Additionally, the HLT requires at least one jet to be b tagged.
In the offline selection, an event must contain a well reconstructed vertex localized within 24 cm in the z direction and 2 cm in the x–y plane around the nominal interaction point. Selected events are required to contain at least six jets, at least two of which have to be tagged as b jets. The sixth jet (jet6), ordered in decreasing pT, must fulfill pT(jet6) > 40 GeV, and HT >450 GeV
is required. The two b jets must be separated in∆R=√∆φ2+∆η2by∆R(bb) >2.0.
The tt signal is simulated at an mtof 172.5 GeV using the POWHEG v2 [27–29] matrix-element
(ME) generator in next-to-leading order (NLO) perturbative quantum chromodynamics (QCD). For the parton distribution functions (PDFs), the NNPDF3.0 NLO set [30] is used with the strong coupling constant value of αS=0.118. This is one of the first PDF sets to include the total
tt cross section measurements from ATLAS and CMS at√s =7 and 8 TeV as input. The parton shower (PS) and hadronization are handled by PYTHIA 8.219 [31] using the CUETP8M2T4 tune [32, 33] and GEANT4 is used to simulate the response of the CMS detector [34]. The simulated signal sample is normalized to the integrated luminosity of the data sample using a cross section of σtt = 832 pb, calculated at next-to-next-to-leading order in QCD including resummation of next-to-next-to-leading logarithmic soft gluon terms [35]. In addition to the default sample, six other samples are used assuming top quark masses of 166.5, 169.5, 171.5, 173.5, 175.5, and 178.5 GeV, and using the corresponding cross sections.
For simulated events, a trigger emulation is used. The residual differences in the trigger effi-ciency between data and simulation are corrected by applying scale factors to the simulated events. These are obtained by measuring the trigger efficiency with respect to a reference HT trigger for both data and simulation. The parameterized ratio as a function of pT(jet6)and
HT is used to reweight the simulated events. Additional pp collisions are included in the
sim-ulated events. These are weighted to match the pileup distribution in data. Finally, corrections to the jet energy scale and resolution, as well as to the b tagging efficiency and misidentification rate, are applied to the simulated events.
4
Kinematic fit and background estimation
To improve the resolution of the top quark mass and decrease the background contribution, a kinematic fit is applied. It exploits the known topology of the signal events, i.e., pair production of a heavy particle and antiparticle, each decaying to Wb with W → qq0. The three-momenta
of the jets are fitted such that χ2=
∑
j∈jets pTrecoj −pTfitj 2 σ2p T j + ηrecoj −ηjfit 2 ση2j + φrecoj −φfitj 2 σφ2 j is minimized, where all jets assigned to the tt decay system are considered. The labels “reco” and “fit” denote the components of the originally reconstructed and the fitted jets, respectively, and the corresponding resolutions are labeled σX. The minimization is performed, constraining
the invariant mass of the jets assigned to each W boson decay to mW = 80.4 GeV. As an
addi-tional constraint, the two top quark candidates are required to have equal invariant masses. All possible parton-jet assignments are tested using the leading six jets in the event, but only b-tagged jets are used as b candidates and equivalent choices (e.g., swapping the two jets origi-nating from one W boson) are not considered separately. Of the remaining 12 possibilities, only the assignment yielding the smallest χ2is used in the following. The χ2value can be used as a
goodness-of-fit (gof) measure. For three degrees of freedom, it is translated into a p-value of Pgof≡1−erf r χ2 2 ! + r 2χ2 π e −χ2/2.
Events are required to fulfill Pgof >0.1 for the best assignment.
In simulation, event generator information can be used to validate the assignment of the re-constructed jets to the top quark decay products. Events are classified accordingly as correct or wrong permutations. A parton-jet assignment is considered correct if the jets can be matched unambiguously to the right partons within∆R < 0.3. Wrong permutations can occur because of a wrong parton-jet assignment, yielding the smallest χ2or jets being out of acceptance, not
being reconstructed, or failing the identification requirements.
The Pgof distribution is displayed in Fig. 1 (right). Requiring Pgof > 0.1 increases the fraction
of correct permutations from 6 to 51%. The fitted top quark mass (mfit
t ) is calculated as the
invariant mass of the corresponding jets returned by the kinematic fit. Compared to the mass calculated from the originally reconstructed jets, the mass resolution is improved from 14.0 to 8.8 GeV for the correct parton-jet assignments, where, in both cases, the same events passing the Pgof >0.1 requirement are used.
The ∆R(bb) > 2.0 and Pgof > 0.1 requirements greatly reduce the background from QCD
multijet production from approximately 80 to 25%, but a significant number of multijet events enters the signal selection owing to the large production cross section of that background con-tribution. These events can fulfill the goodness-of-fit criterion because of combinatorial chance, but not because of an underlying decay topology. Therefore, it is assumed that b jets can be exchanged with light-flavor jets for the estimation of the background from data, because the probability for mimicking the tt topology is the same.
For the background estimation, the same selection as for the signal is applied, as described above, but instead of requiring two b-tagged jets, events with exactly zero b-tagged jets are used. For this veto, a very loose working point is used for the b tagger, to suppress contam-ination from tt events in this QCD-enriched sample. A prescaled trigger similar to the signal trigger is used for this selection, which does not require the presence of b jets. The kinematic fit is applied as before, but here any of the six light-flavor jets can be assigned to the partons originating from the W decays, as well as to the partons serving as b quarks, leading to 90
possible permutations that have to be evaluated. This method allows one to determine the kinematic distributions of the background, but the normalization is unknown. In all plots, the background is normalized to the difference of the number of data events and the number of expected signal events. This data sample contains approximately five times the number of expected background events, so it provides good statistical precision.
b b R ∆ 1 2 3 4 5 6 Data/MC 0.5 1 1.5 Events / 0.1 200 400 600 800 1000 1200 1400 correct t t wrong t t Multijet Data (13 TeV) -1 35.9 fb
CMS
gof P 0 0.2 0.4 0.6 0.8 1 Data/MC 0.5 1 1.5 Events / 0.02 200 400 600 800 1000 tt correct wrong t t Multijet Data (13 TeV) -1 35.9 fbCMS
Figure 1: The∆R(bb)(left) and Pgof (right) distributions of data compared to simulated signal
and the multijet background estimate. For each event, the parton-jet assignment yielding the smallest χ2 in the kinematic fit is used. The simulated signal events are classified as correct or wrong assignments and displayed separately, and the distributions are normalized to the integrated luminosity. For the background estimate, the total normalization is given by the difference of observed data events and expected signal events. The hashed bands represent the total uncertainty in the complete prediction. The lower panels show the ratio of data and prediction.
The final selected data set consists of 10 799 events with a signal purity of 75%. Figure 1 shows the distributions of the separation of the two b jets ∆R(bb) and the quantity Pgof in
data, compared to the background estimate and tt simulation. For the tt signal, correct and wrong parton-jet assignments are shown separately. The corresponding distributions of mfit t
and the reconstructed W boson mass mreco
W , calculated from the originally reconstructed jets,
are shown in Fig. 2. These two quantities are used in the top quark mass extraction described in the following section.
5
Ideogram method
For the extraction of mt, the ideogram method is used [8, 9]. Simultaneously, a JSF is
deter-mined that is used in addition to the standard CMS jet energy calibration [12] to reduce the corresponding systematic uncertainty. The distributions of mfit
t obtained from the kinematic fit
and mrecoW are used in a combined fit. For mrecoW , the average mass of the two W bosons in an event is used.
[GeV] fit t m 100 200 300 400 Data/MC 0.5 1 1.5 Events / 5 GeV 200 400 600 800 1000 1200 1400 1600 1800 tt correct wrong t t Multijet Data (13 TeV) -1 35.9 fb
CMS
[GeV] reco W m 70 80 90 100 110 120 Data/MC 0.5 1 1.5 Events / 1 GeV 200 400 600 800 1000 correct t t wrong t t Multijet Data (13 TeV) -1 35.9 fbCMS
Figure 2: The fitted top quark mass (left) and reconstructed W boson mass (right) distributions of data compared to simulated signal and the multijet background estimate. The shown recon-structed W boson mass is the average mass of the two W bosons in the event. For each event, the parton-jet assignment yielding the smallest χ2in the kinematic fit is used. The simulated
signal events are classified as correct or wrong assignments and displayed separately, and the distributions are normalized to the integrated luminosity. For the background estimate, the to-tal normalization is given by the difference of observed data events and expected signal events. The hashed bands represent the total uncertainty in the prediction. The lower panels show the ratio of data and prediction.
The likelihood L (mt, JSF) =P(sample|mt, JSF) =
∏
events P(event|mt, JSF) =∏
events Pmfitt , mrecoW |mt, JSFis maximized, yielding the best fit values for mtand JSF. A prior probability for the JSF can be
incorporated by maximizing
P(JSF)P(sample|mt, JSF)
instead. Treating mfit
t and mrecoW as uncorrelated, as verified using simulated events, the
proba-bility P mfitt , mrecoW |mt, JSF factorizes into
Pmfitt , mrecoW |mt, JSF = fsigP mfitt , mrecoW |mt, JSF + 1− fsig Pbkg mfitt , mrecoW = fsig
∑
j fjPjmfitt |mt, JSF Pj(mrecoW |mt, JSF) + 1− fsig Pbkg mfitt Pbkg(mrecoW ),where fj with j ∈ {correct, wrong}is the relative fraction of the different permutation cases
The probability densities Pj mfitt |mt, JSF and Pj(mrecoW |mt, JSF)for the signal are described by
analytic functions parametrized in mtand JSF. For the determination of the parameters, a
simul-taneous fit to simulated samples for seven different generated top quark masses mgent and five different input JSF values is used. The background shape is described by a spline interpolation as a function of mfitt and mrecoW , but independent of the model parameters mtand JSF.
Three variations of a maximum likelihood fit are performed to extract the top quark mass. In the one-dimensional (1D) analysis, the JSF is fixed to unity (corresponding to a Dirac delta function for the prior probability), i.e., the standard CMS jet energy calibration. For the two-dimensional (2D) analysis, the JSF is a free parameter in the maximum likelihood fit, making possible a compensation of part of the systematic uncertainties. The signal fraction and correct permutation fraction are free parameters in both cases. The third (hybrid) method is a weighted combination of both approaches, corresponding to a measurement with a Gaussian constraint on the JSF around unity. In the limit of an infinitely narrow JSF constraint, the hybrid method is identical to the 1D method, while for an infinitely broad prior probability distribution, the 2D method is recovered. The width of the Gaussian constraint in the hybrid method is optimized to yield the smallest total uncertainty.
To calibrate the mass extraction method, pseudo-experiments are performed for the seven dif-ferent generated values of mgent and three input JSF values (0.98, 1.00, and 1.02). The extracted mtand JSF values are compared to the input values and the residual slopes in mgent and JSF are
used as calibration. The residual biases after the calibration are shown in Fig. 3 for pseudo-experiments with different JSF and mgent values. As expected, neither a significant residual offset nor a slope are observed after the calibration procedure.
[GeV] t,gen m 166 168 170 172 174 176 178 > [GeV] t,gen -m t,cal <m −0.5 0 0.5 1 [GeV] t,gen m 166 168 170 172 174 176 178 -JSF> cal <JSF 0.01 − 0.005 − 0 0.005 0.01 (13 TeV) -1 35.9 fb simulation CMS JSF=0.98 JSF=1.00 JSF=1.02
Figure 3: Difference between extracted and generated top quark masses (upper panel) and JSFs (lower panel) for different input masses and JSFs after the calibration in the all-jets channel. The values are extracted using the 2D method.
6
Systematic uncertainties
A summary of the systematic uncertainty sources is shown in Table 1. The corresponding values are obtained from pseudo-experiments, using Monte Carlo (MC) signal samples with variations of the individual systematic uncertainty sources. In the following, details for the
de-termination of the most important uncertainties are given. Most systematic uncertainty sources are shifted by±1 standard deviation, and the absolute value of the largest resulting shifts in mt
and JSF are quoted as systematic uncertainties for the measurement. For some uncertainties, different models are compared, and are described individually. The maximum of the statistical uncertainty on the observed shift and the shift itself is used as the systematic uncertainty.
• Method calibration: The quadratic sum of the statistical uncertainty and the residual bias of the calibration curve (shown in Fig. 3) after the calibration is used as the systematic uncertainty.
• JECs: Jet energies are scaled up and down according to the pT- and η-dependent
data/simulation uncertainties [23]. The correlation groups (called Intercalibration, MPFInSitu, and Uncorrelated) follow the recommendations documented in Ref. [36].
• Jet energy resolution: Since the jet energy resolution measured in data is worse than in simulation, the simulation is modified to correct for the difference [23]. The jet energy resolution in the simulation is varied up and down within the uncertainty.
• b tagging: The pT-dependent uncertainty of the b tagging efficiencies and
misiden-tification rates of the CSVv2 b tagger [26] are taken into account by reweighting the simulated events accordingly.
• Pileup: To estimate the uncertainty in the determination of the number of pileup events and the reweighting procedure, the inelastic proton-proton cross section [37] used in the determination is varied by±4.6%.
• Background: An uncertainty in the background prediction is obtained by applying the method to simulation and comparing the obtained estimate to the direct simu-lation, i.e., generated QCD multijet events passing the signal selection. A linear fit to the ratio is consistent with a constant value of unity. The slope is varied up and down within its uncertainty and used to reweight the events used for the determi-nation of the background probability density function.
• Trigger: To estimate the uncertainty in the trigger selection, the data/simulation scale factor described in Section 3 is omitted. Additionally, a base trigger requiring the presence of one muon is used to obtain the correction factor. The maximum of the observed shifts with respect to the nominal correction is quoted as an uncertainty.
• JEC flavor: The difference between Lund string fragmentation and cluster fragmen-tation is evaluated comparing PYTHIA 6.422 [38] and HERWIG++ 2.4 [39]. The jet energy response is compared separately for each jet flavor [23]. Uncertainties for jets from different quark flavors and gluons are added linearly, which takes into account possible differences between the measured JSF, which is mainly sensitive to light quarks and gluons, and the b jet energy scale.
• b jet modeling: The uncertainty associated with the fragmentation of b quarks is split into three components. The Bowler–Lund fragmentation function is varied within its uncertainties as determined by the ALEPH and DELPHI Collaborations [40, 41]. As an alternative model of the fragmentation into b hadrons, the Peterson fragmen-tation function is used and the difference obtained relative to the Bowler–Lund frag-mentation function is assigned as an uncertainty. The third uncertainty source taken into account is the semileptonic b hadron branching fraction, which is varied by
−0.45% and+0.77%, motivated by measurements of B0/B+decays and their corre-sponding uncertainties [42].
• PDF: The 100 PDF replicas of the NNPDF3.0 NLO (αS =0.118)set are used to repeat
uncer-Table 1: List of systematic uncertainties for the all-jets channel. The signs of the shifts (δx = xvariation−xnominal) correspond to the+1 standard deviation variation of the systematic
uncertainty source. For linear sums of the uncertainty groups, the relative signs have been con-sidered. Shifts determined using dedicated samples for the systematic variation are displayed with the corresponding statistical uncertainty.
2D 1D hybrid
δm2Dt δJSF2D δm1Dt δmhybt δJSFhyb
[GeV] [%] [GeV] [GeV] [%]
Experimental uncertainties
Method calibration 0.06 0.2 0.06 0.06 0.2
JEC (quad. sum) 0.18 0.3 0.73 0.15 0.2
– Intercalibration −0.04 −0.1 +0.12 −0.04 −0.1
– MPFInSitu −0.03 0.0 +0.22 +0.08 +0.1
– Uncorrelated −0.17 −0.3 +0.69 +0.12 +0.2
Jet energy resolution −0.09 +0.2 +0.09 −0.04 +0.1
b tagging 0.02 0.0 0.01 0.02 0.0
Pileup −0.06 +0.1 0.00 −0.04 +0.1
Background 0.10 0.1 0.03 0.07 0.1
Trigger +0.04 −0.1 −0.04 +0.02 −0.1
Modeling uncertainties
JEC flavor (linear sum) −0.35 +0.1 −0.31 −0.34 0.0
– light quarks (uds) +0.10 −0.1 −0.01 +0.07 −0.1
– charm +0.03 0.0 −0.01 +0.02 0.0
– bottom −0.29 0.0 −0.29 −0.29 0.0
– gluon −0.19 +0.2 +0.03 −0.13 +0.2
b jet modeling (quad. sum) 0.09 0.0 0.09 0.09 0.0
– b frag. Bowler–Lund −0.07 0.0 −0.07 −0.07 0.0
– b frag. Peterson −0.05 0.0 −0.04 −0.05 0.0
– semileptonic b hadron decays −0.03 0.0 −0.03 −0.03 0.0
PDF 0.01 0.0 0.01 0.01 0.0
Ren. and fact. scales 0.05 0.0 0.04 0.04 0.0
ME/PS matching +0.32±0.20 −0.3 −0.05±0.14 +0.24±0.18 −0.2 ISR PS scale +0.17±0.17 −0.2 +0.13±0.12 +0.12±0.14 −0.1 FSR PS scale +0.22±0.12 −0.2 +0.11±0.08 +0.18±0.11 −0.1
Top quark pT +0.03 0.0 +0.02 +0.03 0.0
Underlying event +0.16±0.19 −0.3 −0.07±0.14 +0.10±0.17 −0.2 Early resonance decays +0.02±0.28 +0.4 +0.38±0.19 +0.13±0.24 +0.3 CR modeling (max. shift) +0.41±0.29 −0.4 −0.43±0.20 −0.36±0.25 −0.3 – “gluon move” (ERD on) +0.41±0.29 −0.4 +0.10±0.20 +0.32±0.25 −0.3 – “QCD inspired” (ERD on) −0.32±0.29 −0.1 −0.43±0.20 −0.36±0.25 −0.1
Total systematic 0.81 0.9 1.03 0.70 0.7
Statistical (expected) 0.21 0.2 0.16 0.20 0.1
Total (expected) 0.83 0.9 1.04 0.72 0.7
tainty. In addition, the αSvalue is changed to 0.117 and 0.119. The maximum of the
PDF uncertainty and the αSvariations is quoted as uncertainty.
• Renormalization and factorization scales: The renormalization and factorization scales for the ME calculation are varied. Both are multiplied independently from each
other, and simultaneously by factors of 0.5 and 2 with respect to the default val-ues. This is achieved by appropriately reweighting simulated events. The quoted uncertainty corresponds to the envelope of the resulting shifts.
• ME/PS matching: The matching of thePOWHEGME calculations to thePYTHIAPS is varied by shifting the parameter hdamp=1.58+−0.660.59[33] within the uncertainties. The
jet response precoT /pgenT as a function of pgenT is rescaled in the variation samples to reproduce the response observed in the default sample.
• ISR PS scale: For initial-state radiation (ISR), the PS scale is varied in PYTHIA. The ISR PS scale is multiplied by factors of 2 and 0.5 in dedicated MC samples.
• FSR PS scale: The PS scale used for final-state radiation (FSR) is scaled up by√2 and down by 1/√2 [32], affecting the fragmentation and hadronization, as well addi-tional jet emission. The jet response is rescaled in the variation samples to reproduce the response observed in the default sample.
• Top quark pT: Recent calculations suggest that the top quark pTspectrum is strongly
affected by next-to-next-to-leading-order effects [43]. The pT of the top quark in
simulation is varied to match the distribution measured by CMS [44, 45] and its impact on the mtmeasurement is quoted as a systematic uncertainty.
• Underlying event: Measurements of the underlying event have been used to tune
PYTHIA parameters describing nonperturbative QCD effects [32, 33]. The
parame-ters of the tune are varied within their uncertainties.
• Early resonance decays: Modeling of color reconnection (CR) introduces systematic uncertainties which are estimated by comparing different CR models and settings. In the default sample, the top quark decay products are not included in the CR pro-cess. This setting is compared to the case of including the decay products by en-abling early resonance decays (ERD) inPYTHIA8.
• CR modeling: In addition to the default model used in PYTHIA8, two alternative CR models are used, namely a model with string formation beyond leading color (“QCD inspired”) [46] and a model allowing the gluons to be moved to another string (“gluon move”) [47]. Underlying event measurements are used to tune the parameters of all models [32, 33]. The largest shifts induced by the variations are assigned as the CR uncertainty.
This approach, as well as the ERD variation, is new relative to the Run 1 results at√ s =7 and 8 TeV, because these CR models have become only recently available in PYTHIA8. The new models were first used to evaluate the mtuncertainty due to CR
in Ref. [17]. Like in this analysis, the same increase in systematic uncertainty with respect to the Run 1 result has been observed.
A summary of the systematic uncertainties described above is given in Table 1. In Ref. [17], an ME generator uncertainty has been considered: Instead of usingPOWHEGv2 as ME generator, the MADGRAPH5 aMC@NLO2.2.2 generator with the FxFx matching scheme is used [48, 49]. The difference between the results obtained with the two generators is δmhybt = +0.31±0.52 for the hybrid method in the all-jets channel. However, this is not significant because of the insufficient statistical precision of the available MADGRAPH5 aMC@NLO sample. Since the radiation after the top quark decay is described by PYTHIA, no significant impact of the ME generator choice is expected beyond the variation of the PS scales and matching. Therefore, no ME generator uncertainty is considered in the total uncertainty of the measurement, but the number is just quoted here as a cross-check.
7
Results
For the 2D fit using the 10 799 tt all-jets candidate events, the extracted parameters are m2Dt =172.43±0.22 (stat+JSF)±0.81 (syst) GeV and
JSF2D =0.996±0.002 (stat)±0.009 (syst). The corresponding 1D and hybrid fits yield instead
m1Dt = 172.13±0.17 (stat)±1.03 (syst) GeV,
mhybt = 172.34±0.20 (stat+JSF)±0.70 (syst) GeV, and JSFhyb= 0.997±0.002 (stat)±0.007 (syst).
In all cases the fitted values for the fraction of correct assignments, as well as the background fraction, are in agreement with the values expected from simulation. The hybrid measurement of 172.34±0.20 (stat+JSF)±0.43 (CR+ERD)±0.55 (syst) GeV is the main result of this analysis, since it is constructed to provide the smallest uncertainty. The color reconnection and early res-onance decay parts are separated from the rest of the systematic uncertainties. Because of the larger data sample used in this analysis, the statistical uncertainty is reduced with respect to the result of mt =172.32±0.25 (stat+JSF)±0.59 (syst) GeV obtained at
√
s=8 TeV. The new result is in good agreement with the value measured at√s = 8 TeV, where a leading-order tt simu-lation has been employed to calibrate the measurement, whereas an NLO simusimu-lation has been used here. The systematic uncertainty is increased with respect to the Run 1 result, because a broader set of CR models has been compared, which have become available inPYTHIA8.
8
Combined measurement with the lepton+jets final state
This measurement is combined with the lepton+jets final state, where only electrons and muons are explicitly considered as leptons, while tau leptons enter the selection only when they decay leptonically. The corresponding analysis for the lepton+jets final state is described in Ref. [17]. All selection and analysis steps are kept unchanged. Since the same method for the mass ex-traction is used, a combination with the all-jets channel at the likelihood level is possible. The total likelihoodLis constructed from the single-channel likelihoodsLi,
L(mt, JSF) = LA(mt, JSF)LL(mt, JSF),
where the indices A and L indicate the all-jets and lepton+jets channel, respectively.
No extra calibration of the mass extraction is performed, but the single-channel calibrations are applied. Figure 4 shows the extracted values for the top quark mass and JSF for different input values as a validation. No residual dependence is observed.
The systematic uncertainties are evaluated as described above for the all-jets channel. For the pseudo-experiments, the systematic uncertainty sources are varied simultaneously for both channels. An exception are uncertainties that only affect a single channel. These uncertainty sources are only varied for the corresponding channel. For the all-jets channel, these are the background and trigger uncertainties. In addition, uncertainties specific to the lepton+jets channel are introduced, including the background and trigger uncertainties, as well as the un-certainties arising from the lepton isolation and identification criteria, and are described in Ref. [17]. The complete list of uncertainties is shown in Table 2. A comparison of the hybrid
[GeV] t,gen m 166 168 170 172 174 176 178 > [GeV] t,gen -m t,cal <m −0.2 0 0.2 0.4 0.6 [GeV] t,gen m 166 168 170 172 174 176 178 -JSF> cal <JSF −0.002 0 0.002 (13 TeV) -1 35.9 fb simulation CMS JSF=0.98 JSF=1.00 JSF=1.02
Figure 4: Difference between extracted and generated top quark masses (upper panel) and JSFs (lower panel) for different input masses and JSFs after the single-channel calibrations for the combined measurement. The values are extracted using the 2D method.
mass uncertainties can be found in Table 3 for the all-jets and lepton+jets channels as well as for the combination. In general, the uncertainties for the combination are smaller than those for the all-jets channel and are close to the lepton+jets uncertainties, as expected because the combination is dominated by this channel. The total uncertainty for the combination is slightly smaller than that for the lepton+jets channel.
The combined measurement yields
m2Dt =172.39±0.08 (stat+JSF)±0.71 (syst) GeV and JSF2D =0.995±0.001 (stat)±0.010 (syst)
for the 2D method and
m1Dt = 171.94±0.05 (stat)±1.07 (syst) GeV,
mhybt = 172.26±0.07 (stat+JSF)±0.61 (syst) GeV, and JSFhyb= 0.996±0.001 (stat)±0.007 (syst)
for the 1D and hybrid fits. The likelihood contours for−2∆ lnL = 2.3, corresponding to the 68% confidence level, in the mt-JSF plane are shown in Fig. 5 for the hybrid measurement
re-sults for the all-jets and lepton+jets channels, as well as for the combination. Additionally, the likelihood profiles are displayed as a function of mt. Both channels are in statistical agreement
Table 2: List of systematic uncertainties for the combined mass extraction. The signs of the shifts (δx = xvariation−xnominal) correspond to the+1 standard deviation variation of the
sys-tematic uncertainty source. For linear sums of the uncertainty groups, the relative signs have been considered. Shifts determined using dedicated samples for the systematic variation are displayed with the corresponding statistical uncertainty.
2D 1D hybrid
δm2Dt δJSF2D δm1Dt δmhybt δJSFhyb
[GeV] [%] [GeV] [GeV] [%]
Experimental uncertainties
Method calibration 0.03 0.0 0.03 0.03 0.0
JEC (quad. sum) 0.12 0.2 0.82 0.17 0.3
– Intercalibration −0.01 0.0 +0.16 +0.04 +0.1
– MPFInSitu −0.01 0.0 +0.23 +0.07 +0.1
– Uncorrelated −0.12 −0.2 +0.77 +0.15 +0.3
Jet energy resolution −0.18 +0.3 +0.09 −0.10 +0.2
b tagging 0.03 0.0 0.01 0.02 0.0 Pileup −0.07 +0.1 +0.02 −0.05 +0.1 All-jets background 0.01 0.0 0.00 0.01 0.0 All-jets trigger +0.01 0.0 0.00 +0.01 0.0 `+jets Background −0.02 0.0 +0.01 −0.01 0.0 `+jets Trigger 0.00 0.0 0.00 0.00 0.0 Lepton isolation 0.00 0.0 0.00 0.00 0.0 Lepton identification 0.00 0.0 0.00 0.00 0.0 Modeling uncertainties
JEC flavor (linear sum) −0.39 +0.1 −0.31 −0.37 +0.1
– light quarks (uds) +0.11 −0.1 −0.01 +0.07 −0.1
– charm +0.03 0.0 −0.01 +0.02 0.0
– bottom −0.31 0.0 −0.31 −0.31 0.0
– gluon −0.22 +0.3 +0.02 −0.15 +0.2
b jet modeling (quad. sum) 0.08 0.1 0.04 0.06 0.1
– b frag. Bowler–Lund −0.06 +0.1 −0.01 −0.05 0.0
– b frag. Peterson −0.03 0.0 0.00 −0.02 0.0
– semileptonic b hadron decays −0.04 0.0 −0.04 −0.04 0.0
PDF 0.01 0.0 0.01 0.01 0.0
Ren. and fact. scales 0.01 0.0 0.02 0.01 0.0
ME/PS matching −0.10±0.08 +0.1 +0.02±0.05 +0.07±0.07 +0.1 ME generator +0.16±0.21 +0.2 +0.32±0.13 +0.21±0.18 +0.1 ISR PS scale +0.07±0.08 +0.1 +0.10±0.05 +0.07±0.07 0.1 FSR PS scale +0.23±0.07 −0.4 −0.19±0.04 +0.12±0.06 −0.3 Top quark pT +0.01 −0.1 −0.06 −0.01 −0.1 Underlying event −0.06±0.07 +0.1 +0.00±0.05 −0.04±0.06 +0.1 Early resonance decays −0.20±0.08 +0.7 +0.42±0.05 −0.01±0.07 +0.5 CR modeling (max. shift) +0.37±0.09 −0.2 +0.22±0.06 +0.33±0.07 −0.1 – “gluon move” (ERD on) +0.37±0.09 −0.2 +0.22±0.06 +0.33±0.07 −0.1 – “QCD inspired” (ERD on) −0.11±0.09 −0.1 −0.21±0.06 −0.14±0.07 −0.1
Total systematic 0.71 1.0 1.07 0.61 0.7
Statistical (expected) 0.08 0.1 0.05 0.07 0.1
Table 3: Comparison of the hybrid mass uncertainties for the all-jets and lepton+jets [17] chan-nels, as well as the combination. The signs of the shifts follow the convention of Tables 1 and 2.
δmhybt [GeV]
all-jets `+jets combination Experimental uncertainties
Method calibration 0.06 0.05 0.03
JEC (quad. sum) 0.15 0.18 0.17
– Intercalibration −0.04 +0.04 +0.04
– MPFInSitu +0.08 +0.07 +0.07
– Uncorrelated +0.12 +0.16 +0.15
Jet energy resolution −0.04 −0.12 −0.10
b tagging 0.02 0.03 0.02 Pileup −0.04 −0.05 −0.05 All-jets background 0.07 − 0.01 All-jets trigger +0.02 − +0.01 `+jets background − +0.02 −0.01 Modeling uncertainties
JEC flavor (linear sum) −0.34 −0.39 −0.37 – light quarks (uds) +0.07 +0.06 +0.07
– charm +0.02 +0.01 +0.02
– bottom −0.29 −0.32 −0.31
– gluon −0.13 −0.15 −0.15
b jet modeling (quad. sum) 0.09 0.12 0.06 – b frag. Bowler–Lund −0.07 −0.05 −0.05 – b frag. Peterson −0.05 +0.04 −0.02 – semileptonic b hadron decays −0.03 +0.10 −0.04
PDF 0.01 0.02 0.01
Ren. and fact. scales 0.04 0.01 0.01
ME/PS matching +0.24 −0.07 +0.07 ME generator − +0.20 +0.21 ISR PS scale +0.14 +0.07 +0.07 FSR PS scale +0.18 +0.13 +0.12 Top quark pT +0.03 −0.01 −0.01 Underlying event +0.17 −0.07 −0.06
Early resonance decays +0.24 −0.07 −0.07 CR modeling (max. shift) −0.36 +0.31 +0.33 – “gluon move” (ERD on) +0.32 +0.31 +0.33 – “QCD inspired” (ERD on) −0.36 −0.13 −0.14
Total systematic 0.70 0.62 0.61
Statistical (expected) 0.20 0.08 0.07
0.995 0.996 0.997 0.998 0.999 1.000 JS F 172.0 172.1 172.2 172.3 172.4 172.5 172.6 172.7 mt[GeV] 0.0 0.5 1.0 1.5 2.0 − 2∆ ln L -2∆ ln L = 2.3
CMS
35.9 fb
−1(13 TeV)
Figure 5: Likelihood contours for−2∆ lnL = 2.3, corresponding to the 68% confidence level, in the mt-JSF plane (upper panel) and the likelihood profiles for the top quark mass (lower
panel), where the level corresponding to one standard deviation (σ) is indicated. The hybrid measurement results for the all-jets and lepton+jets channels, as well as for the combination, are shown.
Just as for the single-channel results, the hybrid measurement provides the best precision and is considered the main result. This is the first top quark mass measurement using the tt lep-ton+jets and all-jets final states combined in a single likelihood function. The largest uncer-tainty contribution is related to the modeling of color reconnection, as it was observed for the all-jets channel and the lepton+jets channel before using the same CR models. Accordingly, the quoted systematic uncertainty is larger than those reported in the most precise combination reported by the CMS Collaboration [12], and comparable to the value reported by the ATLAS Collaboration [50].
9
Summary
A measurement of the top quark mass (mt) using the all-jets final state is presented. The
ana-lyzed data set was collected by the CMS experiment in proton-proton collisions at√s =13 TeV that correspond to an integrated luminosity of 35.9 fb−1. The kinematic properties in each event are reconstructed using a constrained fit that assumes a tt hypothesis, which suppresses the dominant multijet background and improves the mass resolution.
The value of mtand an additional jet energy scale factor (JSF) are extracted using the ideogram
method, which uses the likelihood of the values of mtand JSF in each event to determine these
in good agreement with previous CMS results obtained at√s =7, 8, and 13 TeV. The modeling uncertainties are larger than in the previous measurements at lower center-of-mass energies because of the use of new alternative color reconnection models that were not previously avail-able.
A combined measurement using also the lepton+jets final state results in mt = 172.26±
0.07 (stat+JSF)±0.61 (syst) GeV. This is the first combined mt result obtained in the all-jets
and lepton+jets final states using a single likelihood function.
Acknowledgments
We congratulate our colleagues in the CERN accelerator departments for the excellent perfor-mance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croa-tia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Mon-tenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA).
Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Founda-tion; the A.P. Sloan FoundaFounda-tion; the Alexander von Humboldt FoundaFounda-tion; the Belgian Federal Science Policy Office; the Fonds pour la Formation `a la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technolo-gie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science – EOS” – be.h project n. 30820817; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lend ¨ulet (“Momentum”) Programme and the J´anos Bolyai Research Schol-arship of the Hungarian Academy of Sciences, the New National Excellence Program ´UNKP, the NKFIA research grants 123842, 123959, 124845, 124850, and 125105 (Hungary); the Coun-cil of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mo-bility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Estatal de Fomento de la Investigaci ´on Cient´ıfica y T´ecnica de Excelencia Mar´ıa de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund
for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).
References
[1] CDF Collaboration, “Observation of top quark production in ¯pp collisions”, Phys. Rev. Lett. 74 (1995) 2626, doi:10.1103/PhysRevLett.74.2626,
arXiv:hep-ex/9503002.
[2] D0 Collaboration, “Observation of the top quark”, Phys. Rev. Lett. 74 (1995) 2632, doi:10.1103/PhysRevLett.74.2632, arXiv:hep-ex/9503003.
[3] The ALEPH, CDF, D0, DELPHI, L3, OPAL, SLD Collaborations, the LEP Electroweak Working Group, the Tevatron Electroweak Working Group, and the SLD electroweak and heavy flavour groups, “Precision Electroweak Measurements and Constraints on the Standard Model”, technical report, 2010. arXiv:1012.2367.
[4] M. Baak et al., “The electroweak fit of the standard model after the discovery of a new boson at the LHC”, Eur. Phys. J. C 72 (2012) 2205,
doi:10.1140/epjc/s10052-012-2205-9, arXiv:1209.2716.
[5] M. Baak et al., “The global electroweak fit at NNLO and prospects for the LHC and ILC”, Eur. Phys. J. C 74 (2014) 3046, doi:10.1140/epjc/s10052-014-3046-5,
arXiv:1407.3792.
[6] G. Degrassi et al., “Higgs mass and vacuum stability in the standard model at NNLO”, JHEP 08 (2012) 1, doi:10.1007/JHEP08(2012)098, arXiv:1205.6497.
[7] F. Bezrukov, M. Y. Kalmykov, B. A. Kniehl, and M. Shaposhnikov, “Higgs boson mass and new physics”, JHEP 10 (2012) 140, doi:10.1007/JHEP10(2012)140,
arXiv:1205.2893.
[8] DELPHI Collaboration, “Measurement of the mass and width of the W boson in e+e− collisions at√s = 161 – 209 GeV”, Eur. Phys. J. C 55 (2008) 1,
doi:10.1140/epjc/s10052-008-0585-7, arXiv:0803.2534.
[9] CMS Collaboration, “Measurement of the top-quark mass in tt events with lepton+jets final states in pp collisions at√s=7 TeV”, JHEP 12 (2012) 105,
doi:10.1007/JHEP12(2012)105, arXiv:1209.2319.
[10] CDF Collaboration, “Measurement of the top-quark mass in the all-hadronic channel using the full CDF data set”, Phys. Rev. D 90 (2014) 091101,
doi:10.1103/PhysRevD.90.091101, arXiv:1409.4906.
[11] CMS Collaboration, “Measurement of the top-quark mass in all-jets tt events in pp collisions at√s=7 TeV”, Eur. Phys. J. C 74 (2014) 2758,
doi:10.1140/epjc/s10052-014-2758-x, arXiv:1307.4617.
[12] CMS Collaboration, “Measurement of the top quark mass using proton-proton data at√s = 7 and 8 TeV”, Phys. Rev. D 93 (2016) 072004, doi:10.1103/PhysRevD.93.072004, arXiv:1509.04044.
[13] ATLAS Collaboration, “Measurement of the top-quark mass in the fully hadronic decay channel from ATLAS data at√s =7 TeV”, Eur. Phys. J. C 75 (2015) 158,
doi:10.1140/epjc/s10052-015-3373-1, arXiv:1409.0832.
[14] ATLAS Collaboration, “Top-quark mass measurement in the all-hadronic tt decay channel at√s=8 TeV with the ATLAS detector”, JHEP 09 (2017) 118,
doi:10.1007/JHEP09(2017)118, arXiv:1702.07546.
[15] ATLAS Collaboration, “Measurement of the top quark mass in the t¯t→lepton+jets channel from√s=8 TeV ATLAS data and combination with previous results”, (2018). arXiv:1810.01772. Submitted to Eur. Phys. J. C.
[16] CDF and D0 Collaborations, “Combination of CDF and D0 results on the mass of the top quark using up 9.7 fb−1at the Tevatron”, FERMILAB-CONF-16-298-E,
TEVEWWG/top2016/01, arXiv:1608.01881, 2016.
[17] CMS Collaboration, “Measurement of the top quark mass with lepton+jets final states using pp collisions at√s=13 TeV”, Eur. Phys. J. C 78 (2018) 891,
doi:10.1140/epjc/s10052-018-6332-9, arXiv:1805.01428. [18] CMS Collaboration, “The CMS trigger system”, JINST 12 (2017) P01020,
doi:10.1088/1748-0221/12/01/P01020, arXiv:1609.02366.
[19] CMS Collaboration, “Particle-flow reconstruction and global event description with the CMS detector”, JINST 12 (2017) P10003, doi:10.1088/1748-0221/12/10/P10003, arXiv:1706.04965.
[20] M. Cacciari, G. P. Salam, and G. Soyez, “The anti-kTjet clustering algorithm”, JHEP 04
(2008) 063, doi:10.1088/1126-6708/2008/04/063, arXiv:0802.1189.
[21] M. Cacciari, G. P. Salam, and G. Soyez, “FastJet user manual”, Eur. Phys. J. C 72 (2012) 1896, doi:10.1140/epjc/s10052-012-1896-2, arXiv:1111.6097.
[22] M. Cacciari and G. P. Salam, “Dispelling the N3myth for the ktjet-finder”, Phys. Lett. B 641(2006) 57, doi:10.1016/j.physletb.2006.08.037, arXiv:hep-ph/0512210. [23] CMS Collaboration, “Jet energy scale and resolution in the CMS experiment in pp
collisions at 8 TeV”, JINST 12 (2017) P02014,
doi:10.1088/1748-0221/12/02/P02014, arXiv:1607.03663.
[24] CMS Collaboration, “Jet algorithms performance in 13 TeV data”, CMS Physics Analysis Summary CMS-PAS-JME-16-003, 2017.
[25] CMS Collaboration, “The CMS experiment at the CERN LHC”, JINST 3 (2008) S08004, doi:10.1088/1748-0221/3/08/S08004.
[26] CMS Collaboration, “Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV”, JINST 13 (2018) P05011,
doi:10.1088/1748-0221/13/05/P05011, arXiv:1712.07158.
[27] P. Nason, “A new method for combining NLO QCD with shower Monte Carlo algorithms”, JHEP 11 (2004) 040, doi:10.1088/1126-6708/2004/11/040, arXiv:hep-ph/0409146.
[28] S. Frixione, P. Nason, and C. Oleari, “Matching NLO QCD computations with parton shower simulations: thePOWHEGmethod”, JHEP 11 (2007) 070,
doi:10.1088/1126-6708/2007/11/070, arXiv:0709.2092.
[29] S. Alioli, P. Nason, C. Oleari, and E. Re, “A general framework for implementing NLO calculations in shower Monte Carlo programs: thePOWHEGBOX”, JHEP 06 (2010) 043, doi:10.1007/JHEP06(2010)043, arXiv:1002.2581.
[30] NNPDF Collaboration, “Parton distributions for the LHC Run II”, JHEP 04 (2015) 040, doi:10.1007/JHEP04(2015)040, arXiv:1410.8849.
[31] T. Sj ¨ostrand, S. Mrenna, and P. Z. Skands, “A Brief Introduction to PYTHIA 8.1”, Comput. Phys. Commun. 178 (2008) 852, doi:10.1016/j.cpc.2008.01.036,
arXiv:0710.3820.
[32] P. Skands, S. Carrazza, and J. Rojo, “Tuning PYTHIA 8.1: the Monash 2013 Tune”, Eur. Phys. J. C 74 (2014) 3024, doi:10.1140/epjc/s10052-014-3024-y,
arXiv:1404.5630.
[33] CMS Collaboration, “Investigations of the impact of the parton shower tuning in
PYTHIA8 in the modelling of tt at√s=8 and 13 TeV”, CMS Physics Analysis Summary CMS-PAS-TOP-16-021, 2016.
[34] GEANT4 Collaboration, “GEANT4—a simulation toolkit”, Nucl. Instrum. Meth. A 506 (2003) 250, doi:10.1016/S0168-9002(03)01368-8.
[35] M. Czakon and A. Mitov, “Top++: A program for the calculation of the top-pair cross-section at hadron colliders”, Comput. Phys. Commun. 185 (2014) 2930, doi:10.1016/j.cpc.2014.06.021, arXiv:1112.5675.
[36] ATLAS and CMS Collaborations, “Jet energy scale uncertainty correlations between ATLAS and CMS at 8 TeV”, ATL-PHYS-PUB-2015-049, CMS-PAS-JME-15-001, 2015. [37] CMS Collaboration, “Measurement of the inelastic proton-proton cross section at√s=13
TeV”, JHEP 07 (2018) 161, doi:10.1007/JHEP07(2018)161, arXiv:1802.02613. [38] T. Sj ¨ostrand, S. Mrenna, and P. Skands, “PYTHIA 6.4 physics and manual”, JHEP 05
(2006) 026, doi:10.1088/1126-6708/2006/05/026, arXiv:hep-ph/0603175. [39] M. B¨ahr et al., “Herwig++ physics and manual”, Eur. Phys. J. C 58 (2008) 639,
doi:10.1140/epjc/s10052-008-0798-9, arXiv:0803.0883.
[40] DELPHI Collaboration, “A study of the b-quark fragmentation function with the DELPHI detector at LEP I and an averaged distribution obtained at the Z Pole”, Eur. Phys. J. C 71 (2011) 1557, doi:10.1140/epjc/s10052-011-1557-x, arXiv:1102.4748.
[41] ALEPH Collaboration, “Study of the fragmentation of b quarks into B mesons at the Z peak”, Phys. Lett. B 512 (2001) 30, doi:10.1016/S0370-2693(01)00690-6, arXiv:hep-ex/0106051.
[42] Particle Data Group, “Review of particle physics”, Chin. Phys. C 40 (2016) 100001, doi:10.1088/1674-1137/40/10/100001.
[43] M. Czakon, D. Heymes, and A. Mitov, “High-precision differential predictions for top-quark pairs at the LHC”, Phys. Rev. Lett. 116 (2016) 082003,
[44] CMS Collaboration, “Measurement of differential cross sections for top quark pair production using the lepton+jets final state in proton-proton collisions at 13 TeV”, Phys. Rev. D 95 (2017) 092001, doi:10.1103/PhysRevD.95.092001, arXiv:1610.04191. [45] CMS Collaboration, “Measurement of normalized differential tt cross sections in the
dilepton channel from pp collisions at√s= 13 TeV”, JHEP 04 (2018) 060, doi:10.1007/JHEP04(2018)060, arXiv:1708.07638.
[46] J. R. Christiansen and P. Z. Skands, “String formation beyond leading colour”, JHEP 08 (2015) 003, doi:10.1007/JHEP08(2015)003, arXiv:1505.01681.
[47] S. Argyropoulos and T. Sj ¨ostrand, “Effects of color reconnection on t¯t final states at the LHC”, JHEP 11 (2014) 043, doi:10.1007/JHEP11(2014)043, arXiv:1407.6653. [48] J. Alwall et al., “The automated computation of tree-level and next-to-leading order
differential cross sections, and their matching to parton shower simulations”, JHEP 07 (2014) 079, doi:10.1007/JHEP07(2014)079, arXiv:1405.0301.
[49] R. Frederix and S. Frixione, “Merging meets matching in MC@NLO”, JHEP 12 (2012) 061, doi:10.1007/JHEP12(2012)061, arXiv:1209.6215.
[50] ATLAS Collaboration, “Measurement of the top quark mass in the tt→dilepton channel from√s =8 TeV ATLAS data”, Phys. Lett. B 761 (2016) 350,
A
The CMS Collaboration
Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan
Institut f ¨ur Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Er ¨o, A. Escalante Del Valle, M. Flechl, R. Fr ¨uhwirth1, V.M. Ghete, J. Hrubec, M. Jeitler1, N. Krammer, I. Kr¨atschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Sch ¨ofbeck,
M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki
Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez
Universiteit Antwerpen, Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, A. Lelek, M. Pieters, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel
Vrije Universiteit Brussel, Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, J. De Clercq, K. Deroover, G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs
Universit´e Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G. Fasanella, L. Favart, A. Grebenyuk, A.K. Kalsi, T. Lenzi, J. Luetic, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom, Q. Wang
Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas, D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A. Giammanco, G. Krintiras, V. Lemaitre, A. Magitteri, K. Piotrzkowski, A. Saggio, M. Vidal Marono, P. Vischia, J. Zobec
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
F.L. Alves, G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles
Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M. Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote3, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulistaa, Universidade Federal do ABCb, S˜ao Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa
Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov
University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov
Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan
Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, S.M. Shaheen6, A. Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang6, J. Zhao
State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang
Tsinghua University, Beijing, China
Y. Wang
Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez, C.F. Gonz´alez Hern´andez, M.A. Segura Delgado
University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac
University of Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac
Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A. Starodumov7, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski
Charles University, Prague, Czech Republic
M. Finger8, M. Finger Jr.8
Escuela Politecnica Nacional, Quito, Ecuador
E. Ayala
Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin
Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
H. Abdalla9, S. Khalil10, A. Mohamed10
National Institute of Chemical Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M. Kadastik, M. Raidal, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland
Helsinki Institute of Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkil¨a, T. J¨arvinen, V. Karim¨aki, R. Kinnunen, T. Lamp´en, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lind´en, P. Luukka, T. M¨aenp¨a¨a, H. Siikonen, E. Tuominen, J. Tuominiemi
Lappeenranta University of Technology, Lappeenranta, Finland
T. Tuuva
IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup, E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M. ¨O. Sahin, M. Titov
Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Universit´e Paris-Saclay, Palaiseau, France
A. Abdulsalam11, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C. Charlot, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C. Martin Perez, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, J. Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche
Universit´e de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram12, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, V. Cherepanov, C. Collard, E. Conte12, J.-C. Fontaine12, D. Gel´e, U. Goerlach, M. Jansov´a, A.-C. Le Bihan, N. Tonon, P. Van Hove
Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France
S. Gadrat
Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucl´eaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L. Mirabito, S. Perries, A. Popov13, V. Sordini, G. Touquet, M. Vander Donckt, S. Viret
Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze8
Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8
RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P. Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer
RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh, A. G ¨uth, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H. Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Th ¨uer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Fl ¨ugge, O. Hlushchenko, T. Kress, T. M ¨uller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl14
Deutsches Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K. Beernaert, O. Behnke, U. Behrens, A. Berm ´udez Mart´ınez, D. Bertsche, A.A. Bin Anuar, K. Borras15, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Dom´ınguez Damiani, G. Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo16, A. Geiser, J.M. Grados Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Kr ¨ucker, W. Lange, T. Lenz, J. Leonard, K. Lipka, W. Lohmann17, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V. Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, A. Saibel, M. Savitskyi, P. Saxena, P. Sch ¨utze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A. Vagnerini, M. Van De Klundert, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev
University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, T. Dreyer, A. Ebrahimi, E. Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange, D. Marconi, J. Multhaup, M. Niedziela, C.E.N. Niemeyer, D. Nowatschin, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbr ¨uck, F.M. Stober, M. St ¨over, B. Vormwald, I. Zoi
Karlsruher Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, B. Freund, M. Giffels, M.A. Harrendorf, F. Hartmann14, S.M. Heindl, U. Husemann, I. Katkov13, S. Kudella, S. Mitra, M.U. Mozer, Th. M ¨uller, M. Musich, M. Plagge, G. Quast, K. Rabbertz, M. Schr ¨oder, I. Shvetsov, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, C. W ¨ohrmann, R. Wolf
Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G. Paspalaki
National and Kapodistrian University of Athens, Athens, Greece
A. Agapitos, G. Karathanasis, P. Kontaxakis, A. Panagiotou, I. Papavergou, N. Saoulidou, K. Vellidis
National Technical University of Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos, G. Tsipolitis
University of Io´annina, Io´annina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D. Tsitsonis
MTA-ELTE Lend ¨ulet CMS Particle and Nuclear Physics Group, E ¨otv ¨os Lor´and University, Budapest, Hungary
M. Bart ´ok18, M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O. Sur´anyi, G.I. Veres
Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath19, ´A. Hunyadi, F. Sikler, T. ´A. V´ami, V. Veszpremi, G. Vesztergombi†
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, Z.L. Trocsanyi, B. Ujvari
Indian Institute of Science (IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari
National Institute of Science Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati21, C. Kar, P. Mal, K. Mandal, A. Nayak22, S. Roy Chowdhury, D.K. Sahoo21, S.K. Swain
Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R. Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, A. Mehta, K. Sandeep, S. Sharma, J.B. Singh, A.K. Virdi, G. Walia
University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S. Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma
Saha Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj23, M. Bharti23, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep23, D. Bhowmik, S. Dey, S. Dutt23, S. Dutta, S. Ghosh, M. Maity24, K. Mondal, S. Nandan, A. Purohit, P.K. Rout, A. Roy, G. Saha, S. Sarkar, T. Sarkar24, M. Sharan, B. Singh23, S. Thakur23
Indian Institute of Technology Madras, Madras, India
P.K. Behera, A. Muhammad
Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, D.K. Mishra, P.K. Netrakanti, L.M. Pant, P. Shukla, P. Suggisetti
Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, RavindraKumar Verma
Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Karmakar, S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo
Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S. Sharma
Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M. Mohammadi Na-jafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh26, M. Zeinali
University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald
INFN Sezione di Baria, Universit`a di Barib, Politecnico di Baric, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea, A. Gelmia,b, G. Iasellia,c, M. Incea,b, S. Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa, R. Vendittia, P. Verwilligena
![Table 3: Comparison of the hybrid mass uncertainties for the all-jets and lepton+jets [17] chan- chan-nels, as well as the combination](https://thumb-eu.123doks.com/thumbv2/9libnet/4583206.84391/16.892.214.679.334.1103/table-comparison-hybrid-mass-uncertainties-jets-lepton-combination.webp)
